 ;; range [0.0, 100.0].
 ;;
 ;; The experimental procedure is copied from the paper below. This
-;; procedure uses 70% of the test cases as a training set, and the
+;; procedure uses 70% of the fitness cases as a training set, and the
 ;; remaining 30% as a test set. Each time this file is run, it will
-;; select random training (251 test cases) and test (108 test cases)
-;; sets from the test cases to use throughout the entire run.
+;; select random training (251 fitness cases) and test (108 fitness cases)
+;; sets from the fitness cases to use throughout the entire run.
 ;;
 ;; See this paper for more information about this problem:
 ;; Sara Silva and Leonardo Vanneschi. 2009. Operator equalisation,

;; bioavailability.clj
;;
;; This problem is a symbolic regression problem with 359 test cases
;; over 241 variables. Each test case is a candidate drug compound,
;; with each variable being a bi-dimensional molecule descriptor of
;; that compound. The data file data/bioavailability.txt
;; contains the data, with the last column being the target variable,

        [clojush.pushstate]
        [clojush.interpreter]
        [clojush.random]
        [local-file]
        ;[clojush.evaluate] ;;remove later
        ;[clojush.individual] ;;remove later
        [clojure.math.numeric-tower])
  (:require [clojure.string :as string]
            [clojure-csv.core :as csv]))

